@misc{indiciae86e97eddd975,
  title = {Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi‐Member and Stochastic Parameterizations},
  author = {Behrens, Gunnar [Deutsches Zentrum für Luft‐ und Raumfahrt (DLR) Institut für Physik der Atmosphäre Oberpfaffenhofen Germany, University of Bremen Institute of Environmental Physics (IUP) Bremen Germany] (ORCID:0000000259215327) and Beucler, Tom [Faculty of Geosciences and Environment University of Lausanne Lausanne Switzerland, Expertise Center for Climate Extremes University of Lausanne Lausanne Switzerland] (ORCID:0000000257311040) and Iglesias‐Suarez, Fernando [Deutsches Zentrum für Luft‐ und Raumfahrt (DLR) Institut für Physik der Atmosphäre Oberpfaffenhofen Germany, Predictia Intelligent Data Solutions S.L. Santander Spain] (ORCID:0000000334038245) and Yu, Sungduk [Department of Earth System Science University of California Irvine Irvine CA USA, Intel Labs Multimodal Cognitive AI Research SantaClara CA USA] (ORCID:0000000245063887) and Gentine, Pierre [Department of Earth and Environmental Engineering Columbia University New York NY USA, Earth Institute and Data Science Institute Columbia University New York NY USA] (ORCID:0000000208458345) and Pritchard, Michael [Department of Earth System Science University of California Irvine Irvine CA USA, NVIDIA Santa Clara CA USA] (ORCID:0000000203406327) and Schwabe, Mierk [Deutsches Zentrum für Luft‐ und Raumfahrt (DLR) Institut für Physik der Atmosphäre Oberpfaffenhofen Germany] (ORCID:0000000165655890) and Eyring, Veronika [Deutsches Zentrum für Luft‐ und Raumfahrt (DLR) Institut für Physik der Atmosphäre Oberpfaffenhofen Germany, University of Bremen Institute of Environmental Physics (IUP) Bremen Germany] (ORCID:0000000268874885)},
  year = {2025},
  doi = {10.1029/2024ms004272},
  url = {https://www.osti.gov/biblio/2555915},
  note = {Source identifier: 2555915}
}